Computational Intelligence to Study the Importance of Predictors in White Oat ( &lt;i&gt;Avena Sativa&lt;/i&gt; L.)

Júnior, Antonio Carlos Oscar; Sant’Anna, Isabela de Castro; Silva, Michele Jorge da; Bhering, Leonardo Lopes; Nascimento, Moysés; Carvalho, Ivan Ricardo; Silva, José Antônio Gonzalez da; Cruz, Cosme Damião

doi:10.2139/ssrn.3992957

SSRN Journal

2021

DOI: 10.2139/ssrn.3992957

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Computational Intelligence to Study the Importance of Predictors in White Oat ( <i>Avena Sativa</i> L.)

Antonio Carlos Oscar Júnior¹,

Isabela de Castro Sant’Anna²,

Michele Jorge da Silva³

et al.

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2023

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Cited by 1 publication

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Liquid Source Nitrogen as a More Sustainable Technology for oat Fertilization with Computational Simulation Resource

Henrichsen¹,

Silva²,

Basso³

et al. 2023

RGSA

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Purpose: The objective of the study is to validate the technology of liquid nitrogen source by spraying of foliar absorption in comparison to the standard source urea of root absorption in the oat crop. Adapt the fuzzy logic model and training an artificial neural network to simulate oat productivity, under conditions of nitrogen use with the combined action of rainfall and thermal sum accumulated during the crop cycle. Method/design/approach: The study was conducted in Augusto Pestana, RS, Brazil, in a randomized block design with four replications in a 2x4 factorial, for 2 nitrogen sources (liquid and solid) with 4 doses (0, 30, 60 and 120 kg ha-1), respectively. Solid (urea) and liquid (N-Top®) nitrogen sources were applied at the phenological stage of expanded oat fourth leaf. Results and conclusion: The liquid source nitrogen technology presents results similar to the use of the standard urea source, confirming the possibility of using the nutrient by foliar absorption. The simulation of grain yield by fuzzy logic with the input variables nitrogen dose, thermal sum and precipitation is not adequate for the formulated rule base. The input variables used in the artificial neural network proved to be appropriate in the simulation of oat productivity, with consistent simulation results. Originality/value: unprecedented research that seeks to validate the technology of foliar nitrogen absorption in real conditions of oat cultivation in guaranteeing productivity and less environmental damage. And the use of artificial intelligence as a resource to simulate grain productivity involving biological and environmental indicators in the main oat producing region of Brazil.

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Liquid Source Nitrogen as a More Sustainable Technology for oat Fertilization with Computational Simulation Resource

Henrichsen¹,

Silva²,

Basso³

et al. 2023

RGSA

View full text Add to dashboard Cite

show abstract

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Computational Intelligence to Study the Importance of Predictors in White Oat ( <i>Avena Sativa</i> L.)

Cited by 1 publication

References 24 publications

Liquid Source Nitrogen as a More Sustainable Technology for oat Fertilization with Computational Simulation Resource

Liquid Source Nitrogen as a More Sustainable Technology for oat Fertilization with Computational Simulation Resource

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